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Di Xu

5 papers hereh-index 5128 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author1

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CL1
same name
  • Di Xu — 7 papers, h 10
  • Di Xu — 7 papers, h 4
  • Di Xu — 6 papers, h 3
  • Di Xu — 6 papers, h 4
  • Di Xu — 3 papers, h 6
  • Di Xu — 3 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedBlock-wise LoRA: Revisiting Fine-grained LoRA for Effective Personalization and Stylization in Text-to-Image Generation

1 citations · 1 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025

Kwai Keye-VL 1.5 Technical Report

Biao Yang, Bin Wen, Boyang Ding +58

In recent years, the development of Large Language Models (LLMs) has significantly advanced, extending their capabilities to multimodal tasks through Multimodal Large Language Mode…

cs.CV2025

Kwai Keye-VL Technical Report

Kwai Keye Team, Biao Yang, Bin Wen +57

While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities on static images, they often fall short in comprehending dynamic, information-dense short-form vi…

cs.CV2024

EVLM: An Efficient Vision-Language Model for Visual Understanding

Kaibing Chen, Dong Shen, Hanwen Zhong +14

In the field of multi-modal language models, the majority of methods are built on an architecture similar to LLaVA. These models use a single-layer ViT feature as a visual prompt,…

cs.CV2024★ 1 cited

Block-wise LoRA: Revisiting Fine-grained LoRA for Effective Personalization and Stylization in Text-to-Image Generation

Likun Li, Haoqi Zeng, Changpeng Yang +2

The objective of personalization and stylization in text-to-image is to instruct a pre-trained diffusion model to analyze new concepts introduced by users and incorporate them into…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.